-0.000 282 002 3 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal -0.000 282 002 3(10) to 64 bit double precision IEEE 754 binary floating point representation standard (1 bit for sign, 11 bits for exponent, 52 bits for mantissa)

What are the steps to convert decimal number
-0.000 282 002 3(10) to 64 bit double precision IEEE 754 binary floating point representation (1 bit for sign, 11 bits for exponent, 52 bits for mantissa)

1. Start with the positive version of the number:

|-0.000 282 002 3| = 0.000 282 002 3


2. First, convert to binary (in base 2) the integer part: 0.
Divide the number repeatedly by 2.

Keep track of each remainder.

We stop when we get a quotient that is equal to zero.


  • division = quotient + remainder;
  • 0 ÷ 2 = 0 + 0;

3. Construct the base 2 representation of the integer part of the number.

Take all the remainders starting from the bottom of the list constructed above.

0(10) =


0(2)


4. Convert to binary (base 2) the fractional part: 0.000 282 002 3.

Multiply it repeatedly by 2.


Keep track of each integer part of the results.


Stop when we get a fractional part that is equal to zero.


  • #) multiplying = integer + fractional part;
  • 1) 0.000 282 002 3 × 2 = 0 + 0.000 564 004 6;
  • 2) 0.000 564 004 6 × 2 = 0 + 0.001 128 009 2;
  • 3) 0.001 128 009 2 × 2 = 0 + 0.002 256 018 4;
  • 4) 0.002 256 018 4 × 2 = 0 + 0.004 512 036 8;
  • 5) 0.004 512 036 8 × 2 = 0 + 0.009 024 073 6;
  • 6) 0.009 024 073 6 × 2 = 0 + 0.018 048 147 2;
  • 7) 0.018 048 147 2 × 2 = 0 + 0.036 096 294 4;
  • 8) 0.036 096 294 4 × 2 = 0 + 0.072 192 588 8;
  • 9) 0.072 192 588 8 × 2 = 0 + 0.144 385 177 6;
  • 10) 0.144 385 177 6 × 2 = 0 + 0.288 770 355 2;
  • 11) 0.288 770 355 2 × 2 = 0 + 0.577 540 710 4;
  • 12) 0.577 540 710 4 × 2 = 1 + 0.155 081 420 8;
  • 13) 0.155 081 420 8 × 2 = 0 + 0.310 162 841 6;
  • 14) 0.310 162 841 6 × 2 = 0 + 0.620 325 683 2;
  • 15) 0.620 325 683 2 × 2 = 1 + 0.240 651 366 4;
  • 16) 0.240 651 366 4 × 2 = 0 + 0.481 302 732 8;
  • 17) 0.481 302 732 8 × 2 = 0 + 0.962 605 465 6;
  • 18) 0.962 605 465 6 × 2 = 1 + 0.925 210 931 2;
  • 19) 0.925 210 931 2 × 2 = 1 + 0.850 421 862 4;
  • 20) 0.850 421 862 4 × 2 = 1 + 0.700 843 724 8;
  • 21) 0.700 843 724 8 × 2 = 1 + 0.401 687 449 6;
  • 22) 0.401 687 449 6 × 2 = 0 + 0.803 374 899 2;
  • 23) 0.803 374 899 2 × 2 = 1 + 0.606 749 798 4;
  • 24) 0.606 749 798 4 × 2 = 1 + 0.213 499 596 8;
  • 25) 0.213 499 596 8 × 2 = 0 + 0.426 999 193 6;
  • 26) 0.426 999 193 6 × 2 = 0 + 0.853 998 387 2;
  • 27) 0.853 998 387 2 × 2 = 1 + 0.707 996 774 4;
  • 28) 0.707 996 774 4 × 2 = 1 + 0.415 993 548 8;
  • 29) 0.415 993 548 8 × 2 = 0 + 0.831 987 097 6;
  • 30) 0.831 987 097 6 × 2 = 1 + 0.663 974 195 2;
  • 31) 0.663 974 195 2 × 2 = 1 + 0.327 948 390 4;
  • 32) 0.327 948 390 4 × 2 = 0 + 0.655 896 780 8;
  • 33) 0.655 896 780 8 × 2 = 1 + 0.311 793 561 6;
  • 34) 0.311 793 561 6 × 2 = 0 + 0.623 587 123 2;
  • 35) 0.623 587 123 2 × 2 = 1 + 0.247 174 246 4;
  • 36) 0.247 174 246 4 × 2 = 0 + 0.494 348 492 8;
  • 37) 0.494 348 492 8 × 2 = 0 + 0.988 696 985 6;
  • 38) 0.988 696 985 6 × 2 = 1 + 0.977 393 971 2;
  • 39) 0.977 393 971 2 × 2 = 1 + 0.954 787 942 4;
  • 40) 0.954 787 942 4 × 2 = 1 + 0.909 575 884 8;
  • 41) 0.909 575 884 8 × 2 = 1 + 0.819 151 769 6;
  • 42) 0.819 151 769 6 × 2 = 1 + 0.638 303 539 2;
  • 43) 0.638 303 539 2 × 2 = 1 + 0.276 607 078 4;
  • 44) 0.276 607 078 4 × 2 = 0 + 0.553 214 156 8;
  • 45) 0.553 214 156 8 × 2 = 1 + 0.106 428 313 6;
  • 46) 0.106 428 313 6 × 2 = 0 + 0.212 856 627 2;
  • 47) 0.212 856 627 2 × 2 = 0 + 0.425 713 254 4;
  • 48) 0.425 713 254 4 × 2 = 0 + 0.851 426 508 8;
  • 49) 0.851 426 508 8 × 2 = 1 + 0.702 853 017 6;
  • 50) 0.702 853 017 6 × 2 = 1 + 0.405 706 035 2;
  • 51) 0.405 706 035 2 × 2 = 0 + 0.811 412 070 4;
  • 52) 0.811 412 070 4 × 2 = 1 + 0.622 824 140 8;
  • 53) 0.622 824 140 8 × 2 = 1 + 0.245 648 281 6;
  • 54) 0.245 648 281 6 × 2 = 0 + 0.491 296 563 2;
  • 55) 0.491 296 563 2 × 2 = 0 + 0.982 593 126 4;
  • 56) 0.982 593 126 4 × 2 = 1 + 0.965 186 252 8;
  • 57) 0.965 186 252 8 × 2 = 1 + 0.930 372 505 6;
  • 58) 0.930 372 505 6 × 2 = 1 + 0.860 745 011 2;
  • 59) 0.860 745 011 2 × 2 = 1 + 0.721 490 022 4;
  • 60) 0.721 490 022 4 × 2 = 1 + 0.442 980 044 8;
  • 61) 0.442 980 044 8 × 2 = 0 + 0.885 960 089 6;
  • 62) 0.885 960 089 6 × 2 = 1 + 0.771 920 179 2;
  • 63) 0.771 920 179 2 × 2 = 1 + 0.543 840 358 4;
  • 64) 0.543 840 358 4 × 2 = 1 + 0.087 680 716 8;

We didn't get any fractional part that was equal to zero. But we had enough iterations (over Mantissa limit) and at least one integer that was different from zero => FULL STOP (Losing precision - the converted number we get in the end will be just a very good approximation of the initial one).


5. Construct the base 2 representation of the fractional part of the number.

Take all the integer parts of the multiplying operations, starting from the top of the constructed list above:


0.000 282 002 3(10) =


0.0000 0000 0001 0010 0111 1011 0011 0110 1010 0111 1110 1000 1101 1001 1111 0111(2)

6. Positive number before normalization:

0.000 282 002 3(10) =


0.0000 0000 0001 0010 0111 1011 0011 0110 1010 0111 1110 1000 1101 1001 1111 0111(2)

7. Normalize the binary representation of the number.

Shift the decimal mark 12 positions to the right, so that only one non zero digit remains to the left of it:


0.000 282 002 3(10) =


0.0000 0000 0001 0010 0111 1011 0011 0110 1010 0111 1110 1000 1101 1001 1111 0111(2) =


0.0000 0000 0001 0010 0111 1011 0011 0110 1010 0111 1110 1000 1101 1001 1111 0111(2) × 20 =


1.0010 0111 1011 0011 0110 1010 0111 1110 1000 1101 1001 1111 0111(2) × 2-12


8. Up to this moment, there are the following elements that would feed into the 64 bit double precision IEEE 754 binary floating point representation:

Sign 1 (a negative number)


Exponent (unadjusted): -12


Mantissa (not normalized):
1.0010 0111 1011 0011 0110 1010 0111 1110 1000 1101 1001 1111 0111


9. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


Exponent (unadjusted) + 2(11-1) - 1 =


-12 + 2(11-1) - 1 =


(-12 + 1 023)(10) =


1 011(10)


10. Convert the adjusted exponent from the decimal (base 10) to 11 bit binary.

Use the same technique of repeatedly dividing by 2:


  • division = quotient + remainder;
  • 1 011 ÷ 2 = 505 + 1;
  • 505 ÷ 2 = 252 + 1;
  • 252 ÷ 2 = 126 + 0;
  • 126 ÷ 2 = 63 + 0;
  • 63 ÷ 2 = 31 + 1;
  • 31 ÷ 2 = 15 + 1;
  • 15 ÷ 2 = 7 + 1;
  • 7 ÷ 2 = 3 + 1;
  • 3 ÷ 2 = 1 + 1;
  • 1 ÷ 2 = 0 + 1;

11. Construct the base 2 representation of the adjusted exponent.

Take all the remainders starting from the bottom of the list constructed above.


Exponent (adjusted) =


1011(10) =


011 1111 0011(2)


12. Normalize the mantissa.

a) Remove the leading (the leftmost) bit, since it's allways 1, and the decimal point, if the case.


b) Adjust its length to 52 bits, only if necessary (not the case here).


Mantissa (normalized) =


1. 0010 0111 1011 0011 0110 1010 0111 1110 1000 1101 1001 1111 0111 =


0010 0111 1011 0011 0110 1010 0111 1110 1000 1101 1001 1111 0111


13. The three elements that make up the number's 64 bit double precision IEEE 754 binary floating point representation:

Sign (1 bit) =
1 (a negative number)


Exponent (11 bits) =
011 1111 0011


Mantissa (52 bits) =
0010 0111 1011 0011 0110 1010 0111 1110 1000 1101 1001 1111 0111


Decimal number -0.000 282 002 3 converted to 64 bit double precision IEEE 754 binary floating point representation:

1 - 011 1111 0011 - 0010 0111 1011 0011 0110 1010 0111 1110 1000 1101 1001 1111 0111


How to convert numbers from the decimal system (base ten) to 64 bit double precision IEEE 754 binary floating point standard

Follow the steps below to convert a base 10 decimal number to 64 bit double precision IEEE 754 binary floating point:

  • 1. If the number to be converted is negative, start with its the positive version.
  • 2. First convert the integer part. Divide repeatedly by 2 the positive representation of the integer number that is to be converted to binary, until we get a quotient that is equal to zero, keeping track of each remainder.
  • 3. Construct the base 2 representation of the positive integer part of the number, by taking all the remainders from the previous operations, starting from the bottom of the list constructed above. Thus, the last remainder of the divisions becomes the first symbol (the leftmost) of the base two number, while the first remainder becomes the last symbol (the rightmost).
  • 4. Then convert the fractional part. Multiply the number repeatedly by 2, until we get a fractional part that is equal to zero, keeping track of each integer part of the results.
  • 5. Construct the base 2 representation of the fractional part of the number, by taking all the integer parts of the multiplying operations, starting from the top of the list constructed above (they should appear in the binary representation, from left to right, in the order they have been calculated).
  • 6. Normalize the binary representation of the number, shifting the decimal mark (the decimal point) "n" positions either to the left, or to the right, so that only one non zero digit remains to the left of the decimal mark.
  • 7. Adjust the exponent in 11 bit excess/bias notation and then convert it from decimal (base 10) to 11 bit binary, by using the same technique of repeatedly dividing by 2, as shown above:
    Exponent (adjusted) = Exponent (unadjusted) + 2(11-1) - 1
  • 8. Normalize mantissa, remove the leading (leftmost) bit, since it's allways '1' (and the decimal mark, if the case) and adjust its length to 52 bits, either by removing the excess bits from the right (losing precision...) or by adding extra bits set on '0' to the right.
  • 9. Sign (it takes 1 bit) is either 1 for a negative or 0 for a positive number.

Example: convert the negative number -31.640 215 from the decimal system (base ten) to 64 bit double precision IEEE 754 binary floating point:

  • 1. Start with the positive version of the number:

    |-31.640 215| = 31.640 215

  • 2. First convert the integer part, 31. Divide it repeatedly by 2, keeping track of each remainder, until we get a quotient that is equal to zero:
    • division = quotient + remainder;
    • 31 ÷ 2 = 15 + 1;
    • 15 ÷ 2 = 7 + 1;
    • 7 ÷ 2 = 3 + 1;
    • 3 ÷ 2 = 1 + 1;
    • 1 ÷ 2 = 0 + 1;
    • We have encountered a quotient that is ZERO => FULL STOP
  • 3. Construct the base 2 representation of the integer part of the number by taking all the remainders of the previous dividing operations, starting from the bottom of the list constructed above:

    31(10) = 1 1111(2)

  • 4. Then, convert the fractional part, 0.640 215. Multiply repeatedly by 2, keeping track of each integer part of the results, until we get a fractional part that is equal to zero:
    • #) multiplying = integer + fractional part;
    • 1) 0.640 215 × 2 = 1 + 0.280 43;
    • 2) 0.280 43 × 2 = 0 + 0.560 86;
    • 3) 0.560 86 × 2 = 1 + 0.121 72;
    • 4) 0.121 72 × 2 = 0 + 0.243 44;
    • 5) 0.243 44 × 2 = 0 + 0.486 88;
    • 6) 0.486 88 × 2 = 0 + 0.973 76;
    • 7) 0.973 76 × 2 = 1 + 0.947 52;
    • 8) 0.947 52 × 2 = 1 + 0.895 04;
    • 9) 0.895 04 × 2 = 1 + 0.790 08;
    • 10) 0.790 08 × 2 = 1 + 0.580 16;
    • 11) 0.580 16 × 2 = 1 + 0.160 32;
    • 12) 0.160 32 × 2 = 0 + 0.320 64;
    • 13) 0.320 64 × 2 = 0 + 0.641 28;
    • 14) 0.641 28 × 2 = 1 + 0.282 56;
    • 15) 0.282 56 × 2 = 0 + 0.565 12;
    • 16) 0.565 12 × 2 = 1 + 0.130 24;
    • 17) 0.130 24 × 2 = 0 + 0.260 48;
    • 18) 0.260 48 × 2 = 0 + 0.520 96;
    • 19) 0.520 96 × 2 = 1 + 0.041 92;
    • 20) 0.041 92 × 2 = 0 + 0.083 84;
    • 21) 0.083 84 × 2 = 0 + 0.167 68;
    • 22) 0.167 68 × 2 = 0 + 0.335 36;
    • 23) 0.335 36 × 2 = 0 + 0.670 72;
    • 24) 0.670 72 × 2 = 1 + 0.341 44;
    • 25) 0.341 44 × 2 = 0 + 0.682 88;
    • 26) 0.682 88 × 2 = 1 + 0.365 76;
    • 27) 0.365 76 × 2 = 0 + 0.731 52;
    • 28) 0.731 52 × 2 = 1 + 0.463 04;
    • 29) 0.463 04 × 2 = 0 + 0.926 08;
    • 30) 0.926 08 × 2 = 1 + 0.852 16;
    • 31) 0.852 16 × 2 = 1 + 0.704 32;
    • 32) 0.704 32 × 2 = 1 + 0.408 64;
    • 33) 0.408 64 × 2 = 0 + 0.817 28;
    • 34) 0.817 28 × 2 = 1 + 0.634 56;
    • 35) 0.634 56 × 2 = 1 + 0.269 12;
    • 36) 0.269 12 × 2 = 0 + 0.538 24;
    • 37) 0.538 24 × 2 = 1 + 0.076 48;
    • 38) 0.076 48 × 2 = 0 + 0.152 96;
    • 39) 0.152 96 × 2 = 0 + 0.305 92;
    • 40) 0.305 92 × 2 = 0 + 0.611 84;
    • 41) 0.611 84 × 2 = 1 + 0.223 68;
    • 42) 0.223 68 × 2 = 0 + 0.447 36;
    • 43) 0.447 36 × 2 = 0 + 0.894 72;
    • 44) 0.894 72 × 2 = 1 + 0.789 44;
    • 45) 0.789 44 × 2 = 1 + 0.578 88;
    • 46) 0.578 88 × 2 = 1 + 0.157 76;
    • 47) 0.157 76 × 2 = 0 + 0.315 52;
    • 48) 0.315 52 × 2 = 0 + 0.631 04;
    • 49) 0.631 04 × 2 = 1 + 0.262 08;
    • 50) 0.262 08 × 2 = 0 + 0.524 16;
    • 51) 0.524 16 × 2 = 1 + 0.048 32;
    • 52) 0.048 32 × 2 = 0 + 0.096 64;
    • 53) 0.096 64 × 2 = 0 + 0.193 28;
    • We didn't get any fractional part that was equal to zero. But we had enough iterations (over Mantissa limit = 52) and at least one integer part that was different from zero => FULL STOP (losing precision...).
  • 5. Construct the base 2 representation of the fractional part of the number, by taking all the integer parts of the previous multiplying operations, starting from the top of the constructed list above:

    0.640 215(10) = 0.1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0(2)

  • 6. Summarizing - the positive number before normalization:

    31.640 215(10) = 1 1111.1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0(2)

  • 7. Normalize the binary representation of the number, shifting the decimal mark 4 positions to the left so that only one non-zero digit stays to the left of the decimal mark:

    31.640 215(10) =
    1 1111.1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0(2) =
    1 1111.1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0(2) × 20 =
    1.1111 1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0(2) × 24

  • 8. Up to this moment, there are the following elements that would feed into the 64 bit double precision IEEE 754 binary floating point representation:

    Sign: 1 (a negative number)

    Exponent (unadjusted): 4

    Mantissa (not-normalized): 1.1111 1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0

  • 9. Adjust the exponent in 11 bit excess/bias notation and then convert it from decimal (base 10) to 11 bit binary (base 2), by using the same technique of repeatedly dividing it by 2, as shown above:

    Exponent (adjusted) = Exponent (unadjusted) + 2(11-1) - 1 = (4 + 1023)(10) = 1027(10) =
    100 0000 0011(2)

  • 10. Normalize mantissa, remove the leading (leftmost) bit, since it's allways '1' (and the decimal sign) and adjust its length to 52 bits, by removing the excess bits, from the right (losing precision...):

    Mantissa (not-normalized): 1.1111 1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0

    Mantissa (normalized): 1111 1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100

  • Conclusion:

    Sign (1 bit) = 1 (a negative number)

    Exponent (8 bits) = 100 0000 0011

    Mantissa (52 bits) = 1111 1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100

  • Number -31.640 215, converted from decimal system (base 10) to 64 bit double precision IEEE 754 binary floating point =
    1 - 100 0000 0011 - 1111 1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100